Merge pull request #99 from itsdfish/master

Merge updates for .7.2
StatisticalRethinkingJulia · May 10, 2020 · dc9b1b6 · dc9b1b6
2 parents cc74c4e + 53c169b
commit dc9b1b6
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Showing 4 changed files with 7 additions and 6 deletions.
diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "MCMCBenchmarks"
 uuid = "72ce6e51-3f7f-5ebd-8e88-b86aa3e31c30"
 authors = ["Christopher R. Fisher, Rob J. Goedman"]
-version = "0.7.1"
+version = "0.7.2"
 
 [deps]
 AdvancedHMC = "0bf59076-c3b1-5ca4-86bd-e02cd72cde3d"
@@ -35,7 +35,7 @@ Turing = "fce5fe82-541a-59a6-adf8-730c64b5f9a0"
 AdvancedHMC = "^0.2"
 CSV = "^0.5, 0.6"
 CmdStan = "^5.2, 6.0"
-DataFrames = "^0.19, 0.20, 0.21"
+DataFrames = "0.21.0"
 Distributions = "^0.21, 0.22, 0.23"
 DynamicHMC = "^2.1"
 FillArrays = "^0.8"
@@ -51,7 +51,7 @@ SpecialFunctions = "^0.8, 0.9, 0.10"
 StatsPlots = "^0.12, 0.13, 0.14"
 Tracker = "^0.2"
 TransformVariables = "^0.3"
-Turing = "^0.9, 0.10, 0.11, 0.12"
+Turing = "^0.9, 0.10, 0.11, 0.12.0"
 julia = "^1"
 
 [extras]

diff --git a/src/core_benchmarking.jl b/src/core_benchmarking.jl
@@ -226,7 +226,7 @@ function modifyConfig!(s::AHMCNUTS; Nsamples, Nadapt, delta, autodiff=:forward,
     s.config = Turing.NUTS(Nadapt, delta)
     s.Nsamples = Nsamples
     println("Nsamples" , Nsamples)
-    s.autodiff = autodiff == :reverse ? Turing.setadbackend(:reverse_diff) : Turing.setadbackend(:forward_diff)
+    s.autodiff = autodiff == :reverse ? Turing.setadbackend(:reverse_diff) : Turing.setadbackend(:forwarddiff)
 end
 
 function modifyConfig!(s::CmdStanNUTS; Nsamples, Nadapt, delta, kwargs...)

diff --git a/src/plotting.jl b/src/plotting.jl
@@ -133,7 +133,8 @@ end
 se(x) = std(x)/sqrt(length(x))
 
 function summarize(df, metric, grouping, func)
-    newDF= by(df, grouping, metric=>func)
+    g = groupby(df, grouping)
+    newDF= combine(g, metric=>func)
     yvar = names(newDF)[end]
     return newDF,yvar
 end
diff --git a/test/Gaussian_Models.jl b/test/Gaussian_Models.jl
@@ -62,7 +62,7 @@ function sampleDHMC(obs, N, nsamples, autodiff)
   results = mcmc_with_warmup(Random.GLOBAL_RNG, ∇P, nsamples; reporter = NoProgressReport())
 
   # Undo the transformation to obtain the posterior from the chain.
-  posterior = transform.(trans, results.chain)
+  posterior = TransformVariables.transform.(trans, results.chain)
   return nptochain(results, posterior)
 end